The healthcare sector has seen remarkable shifts as it adapts to evolving patient care needs and business standards. Patients today expect convenience, digital communication tools, and coordinated care. The rise of digital health technologies has made it easier for patients to get involved in their own health journey, and for providers to streamline care processes and share medical information.
Healthcare organizations are adapting to these changes by creating more flexible and robust systems. This includes the adoption of generative artificial intelligence (AI), and at its core, large language models (LLMs), to help organizations accomplish business and clinical goals.
Here are the main priorities and challenges facing healthcare in 2024:
Key Priorities for Healthcare
- Healthcare Equity and Access
It’s a fundamental priority to reduce disparities in healthcare access and outcomes so all individuals, regardless of their socioeconomic status, can receive quality care. This includes addressing barriers, such as geographical location, cost, cultural factors, and other social determinants of health (SDOH).
- Patient-Centered Care
It’s crucial that healthcare organizations provide personalized treatment plans, enhance communication, and offer coordinated care to meet rising patient expectations. Furthermore, patients need to be informed and involved in their healthcare decisions.
- Preventive Care
Providers must shift the focus from treating illnesses to preventing them to improve the overall health of the population and reduce healthcare costs. The encouragement of regular check-ups, vaccinations, and healthy lifestyle choices can have a significant impact, and digital solutions play a significant role in helping patients manage their own preventative care.
- Value-Based Care
It’s essential that the healthcare system as a whole switch from a fee-for-service reimbursement model to a value-based reimbursement model, which ensures that providers are incentivized to provide the most effective care over the most expensive care.
- Data Security and Privacy
With the rise of cyberattacks in healthcare, healthcare organizations are prioritizing cybersecurity. They must ensure that patient information remains secure with robust policies to maintain trust, comply with regulations, and avoid devastating financial losses.
- Digital Transformation
Investing in digital health technologies, like telemedicine, electronic health records, and AI can improve patient care, streamline operations, and reduce the administrative burden on clinicians.
Key Challenges for Healthcare
- Healthcare Workforce Shortages
Shortages of healthcare professionals, including doctors, nurses, and allied health workers can strain healthcare systems, affecting the quality and availability of care. This can also put significant strain on existing staff, as a 2023 National Institute of Health (NIH) study found that 49.9% of healthcare workers experienced burnout; burnout being the highest amongst nurses. What’s more, the employee churn rate at hospitals is 22.7%, significantly higher than the national average of 3.8% across industries.
- Rising Healthcare Costs
The increasing cost of healthcare services and treatments poses a challenge for both consumers and healthcare systems, with healthcare spending increasing by 4.1% in the US 2022. Healthcare expenses are expected to continue climbing, pressuring organizations to find cost-effective solutions without compromising quality. Another issue is inflation, as organizations are forced to pay higher wages to accommodate cost of living demands, they must also increase costs for services to support operating expenses.
- Aging Population
As the global population ages, there is a growing demand for healthcare services, particularly for the elderly, who may require specialized care and management of multiple chronic conditions.
- Increasingly Unhealthy Populations
Although improvements in healthcare treatments have occurred, some research suggests that millennials are the first generation to have a lower life expectancy than the previous generation. Much of this decline can be attributed to the increase in sedentary lifestyles, obesity, and the availability of processed foods.
Benefits of Generative AI for Healthcare Businesses
Healthcare organizations are embracing generative AI technologies to help them adapt to changing demands and improve the healthcare system as a whole. Here are the main benefits of generative AI for healthcare.
- Enhanced Medical Imaging: Generative AI can improve the quality of medical images like MRI and CT scans, aiding in more accurate diagnoses and reducing the need for repeat scans.
- Personalized Treatment Plans: AI algorithms can analyze large datasets to identify personalized treatment options for patients, considering genetics, lifestyle, and medical history.
- Faster Drug Discovery: Generative AI can help identify potential drug candidates more quickly by simulating chemical reactions and predicting biological responses.
- Streamlined Documentation: Generative AI can automate routine tasks like medical transcription and patient record management, reducing the administrative burden on healthcare professionals.
- Improved Patient Experience and Personalization: AI-powered chatbots and virtual assistants can engage with patients, answer common questions, and even schedule appointments, enhancing patient satisfaction and reducing response times.
- Predictive Analytics: Generative AI can identify patterns and trends in patient data, allowing healthcare organizations to anticipate patient needs, manage resources effectively, and improve preventative care.
- Clinical Decision Support: AI can analyze medical literature and data to provide healthcare professionals with decision-making support, leading to better treatment outcomes.
- Task Automation: Generative AI can significantly streamline and automate administrative processes in healthcare. By leveraging chatbots and virtual assistants, as well as automating routine tasks such as scheduling and follow up emails, organizations can reduce the workload for staff and improve efficiency.
- Reduced Costs: Generative AI can help healthcare organizations reduce costs by enhancing efficiency, minimizing errors, and optimizing resource allocation, such as by assisting with right-sizing staff and equipment needs. AI can also help predict patients at risk of readmission, allowing healthcare organizations to take preventive measures that can reduce costly readmissions.
- Increased Competitive Advantage: By adopting generative AI tools that enhance convenience for the patient, organizations can offer more satisfactory healthcare services than their competitors.
- Enhanced Cybersecurity: Perform intelligent threat detection and automated incident response, reducing the workload on security employees and improving security measures and response times.
Top Generative AI Use Cases for Healthcare Businesses
As healthcare systems embrace generative AI tools, they’re able to meet patient demands more quickly, reduce the workload on clinicians, and diagnose and treat ailments more effectively. Here are some of the top use cases for generative AI in healthcare.
- Medical Chatbots
Chatbots are a great way to streamline care operations. They can provide automated responses to frequently asked questions, schedule appointments, suggest relevant resources, and escalate to a human resource when necessary. This can reduce the workload on healthcare staff, allowing practitioners to spend their energy helping the patients in need instead of performing mundane tasks.
- Document Comparison Engines
AI-powered document comparison engines can help healthcare organizations ensure compliance with healthcare regulations by automatically comparing policies, guidelines, and legal documents to check for adherence to standards.
- Co-Creating Medical Documentation
Build more holistic, comprehensive medical records by co-creating reports with specialists based on data culled from large databases and disparate EHR systems. Summarize medical documents, look for data duplications, and perform patient matching.
- Enhancing Medical Imaging
Simplify the imaging process through
automation of analysis, anomalies detection, and radiology assistance. AI tools can help identify early signs of cancer, Alzheimers, and more with more accuracy than the human eye, which can
- Personalized Content Generation
Generate informative, disease-specific content for personalized education to help patients manage their illnesses. Deliver tailored recommendations via email or text to support preventative care and keep patients out of the ER.
Get Started on Your Generative AI Journey in Healthcare
It’s time for healthcare organizations to adopt generative AI tools to meet the evolving needs of patients and stay ahead of the market. Still, adopting AI is more of a marathon than a sprint.
Since AI is only as good as the data it trains on, you’ll need to get your data ready for AI, first and foremost. Then, you’ll need to make sure your AI solution resides in a secure, compliant environment in order to avoid disastrous security breaches and compliance violations.
All of this is time-consuming and complex, but Cloudticity can help you accelerate your AI journey on AWS. Get the data ready, build a secure, compliant foundation, and create a proof of concept. Contact us today to get started with generative AI in healthcare!
